Publication: Multiquadric spline-based interactive segmentation of vascular networks
Issued Date
2016-10-13
Resource Type
ISSN
1557170X
Other identifier(s)
2-s2.0-85009083480
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Mahidol University
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SCOPUS
Bibliographic Citation
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Vol.2016-October, (2016), 5913-5916
Suggested Citation
Sachin Meena, V. B.Surya Prasath, Yasmin M. Kassim, Richard J. Maude, Olga V. Glinskii, Vladislav V. Glinsky, Virginia H. Huxley, Kannappan Palaniappan Multiquadric spline-based interactive segmentation of vascular networks. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Vol.2016-October, (2016), 5913-5916. doi:10.1109/EMBC.2016.7592074 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/43431
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Title
Multiquadric spline-based interactive segmentation of vascular networks
Abstract
© 2016 IEEE. Commonly used drawing tools for interactive image segmentation and labeling include active contours or boundaries, scribbles, rectangles and other shapes. Thin vessel shapes in images of vascular networks are difficult to segment using automatic or interactive methods. This paper introduces the novel use of a sparse set of user-defined seed points (supervised labels) for precisely, quickly and robustly segmenting complex biomedical images. A multiquadric spline-based binary classifier is proposed as a unique approach for interactive segmentation using as features color values and the location of seed points. Epifluorescence imagery of the dura mater microvasculature are difficult to segment for quantitative applications due to challenging tissue preparation, imaging conditions, and thin, faint structures. Experimental results based on twenty epifluorescence images is used to illustrate the benefits of using a set of seed points to obtain fast and accurate interactive segmentation compared to four interactive and automatic segmentation approaches.